The presently disclosed inventive concepts relate to machine translation, and more specifically to improving machine translation via adaptively and proactively replacing and/or supplementing inputs for machine translation platforms and solution.
A plethora of online tools exist to facilitate machine translation of textual information from one language to another. As mobile devices become an increasingly prevalent mechanism to access online tools, translation via mobile devices is a useful extension of pre-existing machine translation solutions.
In addition, as optical sensors embedded with mobile devices become more powerful, a wide variety of image-based technologies are migrating to mobile platforms. Accordingly, some translation tools for mobile applications include the ability to extract textual information from image data, so long as the textual information depicted in the image data is of sufficient quality to allow conventional extraction techniques, such as optical character recognition (OCR), to accurately recognize the characters of the text.
However, due to limitations inherent to the mobile device, and also the variability of conditions surrounding capturing an image using a mobile device, it is often difficult, or even impossible, to capture an image of sufficient quality to allow conventional extraction techniques to accurately recognize the characters of the text. As a result, existing machine translation tools are unable to provide an accurate result in many situations.
Accordingly, it would be beneficial to provide systems and techniques for providing accurate translation results of textual information represented in image data even when the image data are of insufficient quality to allow conventional extraction techniques to accurately recognize the characters of the text.